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Soil quality monitoring and manipulation are important in precision agriculture.This study aims to examine the possibility of assessing the soil parameters in apple-planting regions using spectroscopic methods.The performance of near-infrared (NIR) spectroscopy and mid-infirared (MIR) spectroscopy was studied.A total of 111 soil samples were collected from 11 typical locations in apple-planting regions, apple orchards, and the croplands surrounding them.NIR and MIR spectra, combined with partial least square regression, were used to predict the soil parameters, including organic matter content, pH, and the total amount of As, Cu, Zn, Pb, and Cr.Organic matter and pH have sensitive correlation with As and heavy metals.The NIR model showed a high prediction accuracy for the determination of OM, pH, and As, with an R of 0.89, 0.89, and 0.9, respectively.The prediction of these three parameters by MIR showed reduced accuracy (R=0.77, 0.84, and 0.92, respectively).Heavy metals can also be measured by spectroscopy due to their inter-correlation with organic matter.Both NIR and MIR had high correlation coefficients for the determination of Cu, Zn, and Cr, with standard errors of prediction of 2.95, 10.48,and 9.49 mg.kg-1 for NIR and 3.69, 5.84, and 6.94 mg.kg-1 for MIR, respectively.Pb content behaved differently from the other parameters.Both NIR and MIR underestimated Pb content (R=0.67, 0.56 and SEP=3.46, 2.99).Cu and Zn had a higher correlation with OM and pH and had better prediction results than Pb and Cr.NIR spectra can accurately predict several soil parameters, metallic and nonmetallic, simultaneously.Thus, NIR is more feasible than MIR in analyzing soil paramcters in the study area.